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COMP41815: Introduction to Business Analytics

Type Tied
Level 4
Credits 15
Availability Available in 2025/2026
Module Cap None.
Location Durham
Department Computer Science

Prerequisites

  • None

Corequisites

  • None

Excluded Combinations of Modules

  • None

Aims

  • To introduce students to the key concepts of programming in python
  • To examine how data structures affect the ease of implementation and efficiency of computer programs
  • To give students an in-depth understanding at an advanced level of data structures appropriate to business analytics
  • To examine and understand how companies attempt different business and corporate strategies to achieve or maintain a competitive advantage
  • To give students an in-depth understanding at an advanced level of strategy formulation and implementation under conditions of changing political, economic, sociocultural, and technological conditions, industry competition and firm resources
  • To provide an in-depth understanding and critical evaluation of specialist techniques to aid analysis of the competitive and contextual environment.

Content

  • Programming in python
  • Data structures and their impact on execution time
  • Contested nature of the effective organization
  • Approaches to organizational effectiveness
  • Exploration of Taylorism and its relevance today
  • Shifts in control over time
  • Workforce patterns of change and engagement
  • Process models of change
  • Types of change and sources of resistance to change
  • Analysing the strategic environment
  • Devising and implementing strategic plans
  • Supply chains, networks, layout and flow
  • Planning and control
  • Improvement and risk management
  • Cognitivist and behavioural approaches

Learning Outcomes

Subject-specific Knowledge:

  • By the end of this module, students should:
  • understand the core constructs of imperative programming and how they are used in python
  • have a critical appreciation of the main strengths and weaknesses of a range of programming data structures and how to use them
  • understand various corporate strategies of effective organisation and maintaining a competitive advantage

Subject-specific Skills:

  • By the end of this module, students should be able to:
  • write computer programs in python
  • select appropriate data structures for modelling business scenarios
  • use appropriate tools to manage source code
  • critically assess and examine various corporate strategies
  • critically analyse the non-market environment of business on firms, such as the strategic constraints and opportunities presented by socio-cultural and political developments
  • conduct an in-depth industry analysis and gain advanced understanding of its strengths and limitations

Key Skills:

  • Effective written communication
  • Planning, organising and time-management
  • Problem solving and analysis

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

  • Learning outcomes are met through classroom-based workshops, supported by online resources. The workshops consist of a combination of taught input, groupwork, case studies, discussion and computing labs. Online resources provide preparatory material for the workshops typically consisting of directed reading and video content.
  • The formative assessment consists of classroom-based exercises involving individual and group tasks on specific computer science topics.
  • The summative assessment is a individual written report on the design, implementation, analysis and testing of a program to solve a specified business problem

Teaching Methods and Learning Hours

ActivityNumberFrequencyDurationTotalMonitored
Workshops163 per week2 hours32Yes
Preparation and Reading118 
Total150 

Summative Assessment

Component: CourseworkComponent Weighting: 100%
ElementLength / DurationElement WeightingResit Opportunity
Assignment1500 words maximum100

Formative Assessment

Classroom-based exercises involving individual and group analyses and presentations on specific business analytics topics relevant to the learning outcomes of the modules. Oral and written feedback will be given on a group and/or individual basis as appropriate.

More information

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